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A challenge, in the era of economic crisis and uncertainty, is to provide health care services in an efficient and effective manner. The protection of public health, the provision of quality healthcare services to patients, the location of health centers, the geographical distribution of patients, and the provision of specialist services are some of the topics that the government and/or a health organization responsible for health care services provision has to arrange. Other topics are the assessment of quality, safety, and effectiveness of healthcare services provided by healthcare providers. Moreover, a central pylon in designing healthcare policy is expenditure monitoring and control. However, among all these topics the most significant is the protection of public health; especially now that viruses such as Coronavirus are spreading rapidly worldwide. This paper aims to review the use of Statistical Process Monitoring techniques in the public health domain in order to improve health care decision-making under uncertainty and further on to provide an innovative three-layer framework for the collection, processing, and real-time analysis of related data like Coronavirus or any other infectious disease that will emerge in the future for both proper and effective case management and effective health policy planning.

Surveilling public health through statistical process monitoring: A literature review and a unified framework